High-throughput screening (HTS)-based spectrophotometric direct peptide reactivity assay (Spectro-DPRA) to predict human skin sensitization potential

被引:12
作者
Cho, Sun-A [1 ,2 ]
An, Susun [1 ]
Park, Jae-Hak [1 ]
机构
[1] AmorePacific Corp R&D Unit, Safety & Microbiol Lab, Safety & Regulatory Res Div, Yongin, South Korea
[2] Seoul Natl Univ, Coll Vet Med, Res Inst Vet Sci, Dept Lab Anim Med,BK21 PLUS Program Creat Vet Sci, Seoul 08826, South Korea
关键词
Skin sensitization; Peptide reactivity; Spectrophotometric; Animal alternative; IN-VITRO PREDICTION; HUMAN SERUM-ALBUMIN; CONTACT ALLERGENS; GUINEA-PIG; CHEMICALS; IDENTIFICATION; PROTEIN; ADDUCTS; POTENCY; BINDING;
D O I
10.1016/j.toxlet.2019.07.014
中图分类号
R99 [毒物学(毒理学)];
学科分类号
100405 ;
摘要
Some cosmetic ingredients can act as a chemical hapten to induce an immune response; therefore, evaluating the sensitizing potential of cosmetic ingredients is essential. We previously developed a novel in chemico direct peptide reactivity assay involving a spectrophotometric evaluation (Spectro-DPRA) for animal skin sensitization tests (local lymph node assay; LLNA). Based on previous research, we expanded the test materials to confirm the effectiveness of the Spectro-DPRA method for predicting the animal skin sensitization potential, and further determined the feasibility of the method for estimating the human skin sensitization potential. Spectro-DPRA showed 83.1% or 89.1% accuracy compared to a conventional LLNA or prediction based on human data, respectively, with a combination model using both a cysteine peptide and lysine peptide cut-off. To identify the effect of the lipophilicity of a chemical on predicting the skin sensitization potential, we applied our prediction model to chemicals with a Log P-ow range of -1 to 4. Overall predictability was increased, and the accuracy compared to the LLNA and human data was 91.5% and 94.9%, respectively, in the combination cut-off prediction model. In conclusion, Spectro-DPRA serves as an easy, rapid, and high-throughput in chemico screening method with high accuracy to predict the human skin sensitization potential of chemicals.
引用
收藏
页码:27 / 36
页数:10
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